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<div class="header">
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<a href="#pub-attribs">Data Fields</a>  </div>
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<div class="title">ailayer_dense Struct Reference</div>  </div>
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<p>General <a class="el" href="ailayer__dense_8h.html">Dense layer </a> structure.  
 <a href="structailayer__dense.html#details">More...</a></p>

<p><code>#include &lt;<a class="el" href="ailayer__dense_8h_source.html">ailayer_dense.h</a>&gt;</code></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-attribs"></a>
Data Fields</h2></td></tr>
<tr class="memitem:ab13782a46e3804246bf82a92955096b3"><td class="memItemLeft" align="right" valign="top"><a id="ab13782a46e3804246bf82a92955096b3"></a>
<a class="el" href="structailayer.html">ailayer_t</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#ab13782a46e3804246bf82a92955096b3">base</a></td></tr>
<tr class="memdesc:ab13782a46e3804246bf82a92955096b3"><td class="mdescLeft">&#160;</td><td class="mdescRight">Inherited field members from general ailayer struct. <br /></td></tr>
<tr class="separator:ab13782a46e3804246bf82a92955096b3"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab733a6d9451ea97c43c593a495f26d51"><td class="memItemLeft" align="right" valign="top"><a id="ab733a6d9451ea97c43c593a495f26d51"></a>
uint16_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#ab733a6d9451ea97c43c593a495f26d51">result_shape</a> [2]</td></tr>
<tr class="memdesc:ab733a6d9451ea97c43c593a495f26d51"><td class="mdescLeft">&#160;</td><td class="mdescRight">Inference result tensor (<a class="el" href="structailayer.html#a1ed86d1fec7aae68bc79c55f3f965790" title="The result of the forward function is stored here.">ailayer.result</a>) shape. <br /></td></tr>
<tr class="separator:ab733a6d9451ea97c43c593a495f26d51"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr><td colspan="2"><div class="groupHeader">Layer configuration</div></td></tr>
<tr><td colspan="2"><div class="groupText"><p>Required configuration parameters for the layer</p>
<p>These fields have to be configured by the user before calling the initializer function. </p>
</div></td></tr>
<tr class="memitem:aa7ae0d08cc0a75b22e656b9e2e3c336b"><td class="memItemLeft" align="right" valign="top"><a id="aa7ae0d08cc0a75b22e656b9e2e3c336b"></a>
uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#aa7ae0d08cc0a75b22e656b9e2e3c336b">neurons</a></td></tr>
<tr class="memdesc:aa7ae0d08cc0a75b22e656b9e2e3c336b"><td class="mdescLeft">&#160;</td><td class="mdescRight">Layer neurons count (number of outputs). <br /></td></tr>
<tr class="separator:aa7ae0d08cc0a75b22e656b9e2e3c336b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr><td colspan="2"><div class="groupHeader">Trainable parameters</div></td></tr>
<tr><td colspan="2"><div class="groupText"><p>Data fields for the trainable parameters (weights, bias) of the layer </p>
</div></td></tr>
<tr class="memitem:abaaf545fb7c9d3a0b80aa5a460202e04"><td class="memItemLeft" align="right" valign="top"><a id="abaaf545fb7c9d3a0b80aa5a460202e04"></a>
<a class="el" href="structaitensor.html">aitensor_t</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#abaaf545fb7c9d3a0b80aa5a460202e04">weights</a></td></tr>
<tr class="memdesc:abaaf545fb7c9d3a0b80aa5a460202e04"><td class="mdescLeft">&#160;</td><td class="mdescRight">Tensor containing the layer weights. <br /></td></tr>
<tr class="separator:abaaf545fb7c9d3a0b80aa5a460202e04"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a87664225b3b1ad7ec4cb74cc8bd8f349"><td class="memItemLeft" align="right" valign="top"><a id="a87664225b3b1ad7ec4cb74cc8bd8f349"></a>
<a class="el" href="structaitensor.html">aitensor_t</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#a87664225b3b1ad7ec4cb74cc8bd8f349">bias</a></td></tr>
<tr class="memdesc:a87664225b3b1ad7ec4cb74cc8bd8f349"><td class="mdescLeft">&#160;</td><td class="mdescRight">Tensor containing the layer bias weights. <br /></td></tr>
<tr class="separator:a87664225b3b1ad7ec4cb74cc8bd8f349"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a055e3841d49ce4e2d8c52f4bf4536641"><td class="memItemLeft" align="right" valign="top"><a id="a055e3841d49ce4e2d8c52f4bf4536641"></a>
uint16_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#a055e3841d49ce4e2d8c52f4bf4536641">weights_shape</a> [2]</td></tr>
<tr class="memdesc:a055e3841d49ce4e2d8c52f4bf4536641"><td class="mdescLeft">&#160;</td><td class="mdescRight">Weights tensor shape (n x m matrix). <br /></td></tr>
<tr class="separator:a055e3841d49ce4e2d8c52f4bf4536641"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2f0b1dbeba330cf6ef798b0f91cd0a80"><td class="memItemLeft" align="right" valign="top"><a id="a2f0b1dbeba330cf6ef798b0f91cd0a80"></a>
uint16_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#a2f0b1dbeba330cf6ef798b0f91cd0a80">bias_shape</a> [1]</td></tr>
<tr class="memdesc:a2f0b1dbeba330cf6ef798b0f91cd0a80"><td class="mdescLeft">&#160;</td><td class="mdescRight">Bias weights tensor shape (n x m matrix). <br /></td></tr>
<tr class="separator:a2f0b1dbeba330cf6ef798b0f91cd0a80"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afcc6c64ff572ae7408fe1c4bcfe7b9d1"><td class="memItemLeft" align="right" valign="top"><a id="afcc6c64ff572ae7408fe1c4bcfe7b9d1"></a>
<a class="el" href="structaitensor.html">aitensor_t</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#afcc6c64ff572ae7408fe1c4bcfe7b9d1">trainable_params</a> [2]</td></tr>
<tr class="memdesc:afcc6c64ff572ae7408fe1c4bcfe7b9d1"><td class="mdescLeft">&#160;</td><td class="mdescRight">Pointer to the weights and biases (which are the trainable parameters). <br /></td></tr>
<tr class="separator:afcc6c64ff572ae7408fe1c4bcfe7b9d1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a33b189c78566d57ad498dbf2cc364917"><td class="memItemLeft" align="right" valign="top"><a id="a33b189c78566d57ad498dbf2cc364917"></a>
<a class="el" href="structaitensor.html">aitensor_t</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#a33b189c78566d57ad498dbf2cc364917">gradients</a> [2]</td></tr>
<tr class="memdesc:a33b189c78566d57ad498dbf2cc364917"><td class="mdescLeft">&#160;</td><td class="mdescRight">Gradients structure for the back propagation algorithm. <br /></td></tr>
<tr class="separator:a33b189c78566d57ad498dbf2cc364917"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a590c48e998a8a740439e38d0aa4302dd"><td class="memItemLeft" align="right" valign="top"><a id="a590c48e998a8a740439e38d0aa4302dd"></a>
void *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#a590c48e998a8a740439e38d0aa4302dd">optimem</a> [2]</td></tr>
<tr class="memdesc:a590c48e998a8a740439e38d0aa4302dd"><td class="mdescLeft">&#160;</td><td class="mdescRight">Memory field used by the trainings optimizer. <br /></td></tr>
<tr class="separator:a590c48e998a8a740439e38d0aa4302dd"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr><td colspan="2"><div class="groupHeader">Math functions</div></td></tr>
<tr><td colspan="2"><div class="groupText"><p>Required data type specific math functions </p>
</div></td></tr>
<tr class="memitem:a7218a352357b1fb602775252d8286ce6"><td class="memItemLeft" align="right" valign="top">void(*&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#a7218a352357b1fb602775252d8286ce6">linear</a> )(const <a class="el" href="structaitensor.html">aitensor_t</a> *a, const <a class="el" href="structaitensor.html">aitensor_t</a> *b, const <a class="el" href="structaitensor.html">aitensor_t</a> *c, <a class="el" href="structaitensor.html">aitensor_t</a> *result)</td></tr>
<tr class="memdesc:a7218a352357b1fb602775252d8286ce6"><td class="mdescLeft">&#160;</td><td class="mdescRight">Required math function: Linear transformation.  <a href="structailayer__dense.html#a7218a352357b1fb602775252d8286ce6">More...</a><br /></td></tr>
<tr class="separator:a7218a352357b1fb602775252d8286ce6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa401e714d435b2673670e3be35da33c1"><td class="memItemLeft" align="right" valign="top">void(*&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#aa401e714d435b2673670e3be35da33c1">mat_mul_at</a> )(const <a class="el" href="structaitensor.html">aitensor_t</a> *a, const <a class="el" href="structaitensor.html">aitensor_t</a> *b, <a class="el" href="structaitensor.html">aitensor_t</a> *result)</td></tr>
<tr class="memdesc:aa401e714d435b2673670e3be35da33c1"><td class="mdescLeft">&#160;</td><td class="mdescRight">Required math function: Matrix multiplication with transposed a.  <a href="structailayer__dense.html#aa401e714d435b2673670e3be35da33c1">More...</a><br /></td></tr>
<tr class="separator:aa401e714d435b2673670e3be35da33c1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a422118d4ddc5559465a4a411dc20bcb5"><td class="memItemLeft" align="right" valign="top">void(*&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#a422118d4ddc5559465a4a411dc20bcb5">mat_mul_bt</a> )(const <a class="el" href="structaitensor.html">aitensor_t</a> *a, const <a class="el" href="structaitensor.html">aitensor_t</a> *b, <a class="el" href="structaitensor.html">aitensor_t</a> *result)</td></tr>
<tr class="memdesc:a422118d4ddc5559465a4a411dc20bcb5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Required math function: Matrix multiplication with transposed b.  <a href="structailayer__dense.html#a422118d4ddc5559465a4a411dc20bcb5">More...</a><br /></td></tr>
<tr class="separator:a422118d4ddc5559465a4a411dc20bcb5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7674445f16490c6cacdb03157feab8c7"><td class="memItemLeft" align="right" valign="top">void(*&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#a7674445f16490c6cacdb03157feab8c7">tensor_add</a> )(const <a class="el" href="structaitensor.html">aitensor_t</a> *a, const <a class="el" href="structaitensor.html">aitensor_t</a> *b, <a class="el" href="structaitensor.html">aitensor_t</a> *result)</td></tr>
<tr class="memdesc:a7674445f16490c6cacdb03157feab8c7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Required math function: Element wise tensor addition.  <a href="structailayer__dense.html#a7674445f16490c6cacdb03157feab8c7">More...</a><br /></td></tr>
<tr class="separator:a7674445f16490c6cacdb03157feab8c7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4c1ea5c9637a2a0d708442e852bba4ab"><td class="memItemLeft" align="right" valign="top">void(*&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structailayer__dense.html#a4c1ea5c9637a2a0d708442e852bba4ab">sum_channelwise</a> )(const <a class="el" href="structaitensor.html">aitensor_t</a> *a, int8_t channel_axis, <a class="el" href="structaitensor.html">aitensor_t</a> *result)</td></tr>
<tr class="memdesc:a4c1ea5c9637a2a0d708442e852bba4ab"><td class="mdescLeft">&#160;</td><td class="mdescRight">Required math function: Channel-wise sum.  <a href="structailayer__dense.html#a4c1ea5c9637a2a0d708442e852bba4ab">More...</a><br /></td></tr>
<tr class="separator:a4c1ea5c9637a2a0d708442e852bba4ab"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>General <a class="el" href="ailayer__dense_8h.html">Dense layer </a> structure. </p>
</div><h2 class="groupheader">Field Documentation</h2>
<a id="a7218a352357b1fb602775252d8286ce6"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a7218a352357b1fb602775252d8286ce6">&#9670;&nbsp;</a></span>linear</h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void(* linear) (const <a class="el" href="structaitensor.html">aitensor_t</a> *a, const <a class="el" href="structaitensor.html">aitensor_t</a> *b, const <a class="el" href="structaitensor.html">aitensor_t</a> *c, <a class="el" href="structaitensor.html">aitensor_t</a> *result)</td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Required math function: Linear transformation. </p>
<p>Requires a math function that performs a linear transformation:<br  />
 </p><p class="formulaDsp">
\[ result = a \cdot b \oplus c = a \cdot b + \left( \begin{array}{c} 1 \\ \vdots \\ 1 \\ \end{array}\right) \cdot c \]
</p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">a</td><td>Matrix with dimension \( N \times K \) (input) </td></tr>
    <tr><td class="paramname">b</td><td>Matrix with dimension \( K \times M \) (input) </td></tr>
    <tr><td class="paramname">c</td><td>Laying vektor with dimension \( 1 \times M \) (input) </td></tr>
    <tr><td class="paramname">result</td><td>Matrix with dimension \( N \times M \) (output) </td></tr>
  </table>
  </dd>
</dl>

</div>
</div>
<a id="aa401e714d435b2673670e3be35da33c1"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aa401e714d435b2673670e3be35da33c1">&#9670;&nbsp;</a></span>mat_mul_at</h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void(* mat_mul_at) (const <a class="el" href="structaitensor.html">aitensor_t</a> *a, const <a class="el" href="structaitensor.html">aitensor_t</a> *b, <a class="el" href="structaitensor.html">aitensor_t</a> *result)</td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Required math function: Matrix multiplication with transposed a. </p>
<p>Requires a math function that performs a matrix multiplication on two 2D tensors:<br  />
 </p><p class="formulaDsp">
\[ result = a^T \cdot b \]
</p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">a</td><td>Matrix with dimension \( K \times N \) (input) </td></tr>
    <tr><td class="paramname">b</td><td>Matrix with dimension \( K \times M \) (input) </td></tr>
    <tr><td class="paramname">result</td><td>Matrix with dimension \( N \times M \) (output) </td></tr>
  </table>
  </dd>
</dl>

</div>
</div>
<a id="a422118d4ddc5559465a4a411dc20bcb5"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a422118d4ddc5559465a4a411dc20bcb5">&#9670;&nbsp;</a></span>mat_mul_bt</h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void(* mat_mul_bt) (const <a class="el" href="structaitensor.html">aitensor_t</a> *a, const <a class="el" href="structaitensor.html">aitensor_t</a> *b, <a class="el" href="structaitensor.html">aitensor_t</a> *result)</td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Required math function: Matrix multiplication with transposed b. </p>
<p>Requires a math function that performs a matrix multiplication on two 2D tensors:<br  />
 </p><p class="formulaDsp">
\[ result = a \cdot b^T \]
</p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">a</td><td>Matrix with dimension \( N \times K \) (input) </td></tr>
    <tr><td class="paramname">b</td><td>Matrix with dimension \( M \times K \) (input) </td></tr>
    <tr><td class="paramname">result</td><td>Matrix with dimension \( N \times M \) (output) </td></tr>
  </table>
  </dd>
</dl>

</div>
</div>
<a id="a4c1ea5c9637a2a0d708442e852bba4ab"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a4c1ea5c9637a2a0d708442e852bba4ab">&#9670;&nbsp;</a></span>sum_channelwise</h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void(* sum_channelwise) (const <a class="el" href="structaitensor.html">aitensor_t</a> *a, int8_t channel_axis, <a class="el" href="structaitensor.html">aitensor_t</a> *result)</td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Required math function: Channel-wise sum. </p>
<p>Requires a math function that calculates the sum of all elements of each channel c. The result tensor is 1D.: </p><p class="formulaDsp">
\[ result_c = \sum_i(a_{ci}) \]
</p>
 
</div>
</div>
<a id="a7674445f16490c6cacdb03157feab8c7"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a7674445f16490c6cacdb03157feab8c7">&#9670;&nbsp;</a></span>tensor_add</h2>

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          <td class="memname">void(* tensor_add) (const <a class="el" href="structaitensor.html">aitensor_t</a> *a, const <a class="el" href="structaitensor.html">aitensor_t</a> *b, <a class="el" href="structaitensor.html">aitensor_t</a> *result)</td>
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<p>Required math function: Element wise tensor addition. </p>
<p>Requires a math function that adds two tensors element-wise: </p><p class="formulaDsp">
\[ result = a + b \]
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<hr/>The documentation for this struct was generated from the following file:<ul>
<li><a class="el" href="ailayer__dense_8h_source.html">ailayer_dense.h</a></li>
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